Structural variants (Cancer GIAB) part 2: copy number

JBrowse v5 beta

The tutorials target the JBrowse v5 beta, and the v4.3.0 release on the download page lacks some of what they show. To install the beta of JBrowse Web, run npm install -g @jbrowse/cli@next, then jbrowse create jbrowse2 --branch v5.0.0-beta.15. Desktop beta builds are coming soon.

HG008-T, the tumor of the C-GIAB matched pair, is hypodiploid: 35 chromosomes down from 46, with widespread arm-level loss (Wagner et al. 2026). C-GIAB publishes copy-number calls on it from four groups. Starting from the assembly, reads and benchmark that part 1 loads, we:

load four copy-number callsets as tracks: DRAGEN's segments, NYGC's segments and log2 ratio, Wakhan's copy number per haplotype, and the benchmark's absolute copy number
build binned depth from the reads with HiFiCNV and B-allele frequency with bcftools, and load both beside the callsets
load tumor and matched-normal coverage as overlapping scatter tracks
check copy number at four driver genes, CDKN2A, TP53, SMAD4 and KRAS, against depth and B-allele frequency

Prerequisites

The walkthroughs also run on the hosted C-GIAB demo. Building your own instance needs:

The JBrowse instance, assembly, CRAMs and benchmark tracks that part 1 builds
The command-line tools below, with the versions tested in parentheses:
- megadepth (v1.2.0 or later), for the coverage tracks
- HiFiCNV (v1.0 or later), for the binned depth track
- bcftools (v1.21 or later), for the B-allele frequency track
- tabix (v1.21 or later), to index the heterozygous sites
- bedGraphToBigWig from the UCSC utilities

# Debian/Ubuntu
sudo apt install bcftools tabix
# or conda, which has every tool above
conda install -c bioconda -c conda-forge bcftools htslib \
  ucsc-bedgraphtobigwig megadepth hificnv
# or Linux x86_64 binaries for the tools apt lacks
wget -P ~/.local/bin \
  https://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/bedGraphToBigWig
chmod +x ~/.local/bin/bedGraphToBigWig

The data

The copy-number call sets are on the C-GIAB FTP, and the tracks over them read the files by URL. The depth, B-allele frequency and coverage tracks read local files that the commands below write from the CRAMs of part 1, so run the build script first, or follow the same commands on your own reads.

What it is	File
The V0.5 draft benchmark SV and CNV calls	NIST_HG008-T_somatic-stvar-CNV_DraftBenchmark_V0.5-20260318/
DRAGEN's somatic SV and CNV calls (Illumina)	standard/
NYGC's somatic SVs, annotated CNV segments and BIC-seq2 log2 ratio (Illumina)	GRCh38-GIABv3/
Wakhan's haplotype-specific copy number and LOH segments (HiFi phased with Hi-C)	bed_output/
The earlier Wakhan run's Clair3 tumor small-variant calls	merge_output_tumor.vcf.gz
The normal's germline calls	HG008-N-P.GRCh38.deepvariant.phased.vcf.gz

Installing megadepth and HiFiCNV

Two prerequisites install from release binaries:

wget https://github.com/ChristopherWilks/megadepth/releases/download/1.2.0/megadepth
chmod +x megadepth && sudo mv megadepth /usr/local/bin/
# --strip-components=1: drop the top-level folder of the release tarball
# --wildcards '*/hificnv': extract the binary alone
curl -L https://github.com/PacificBiosciences/HiFiCNV/releases/download/v1.0.1/hificnv-v1.0.1-x86_64-unknown-linux-gnu.tar.gz \
  | tar xz --strip-components=1 -C /usr/local/bin --wildcards '*/hificnv'

Coverage bigWigs from the CRAMs

megadepth writes each CRAM's per-base coverage as a bigWig, which the driver-gene tracks below read:

megadepth HG008-T.cram --bigwig

Copy number from the published callsets

C-GIAB publishes copy-number calls on this pair from four groups:

Callset	Called from	Each segment has
NIST V0.5 draft benchmark	assembly comparison plus read support	absolute total and per-haplotype copy number
Wakhan	PacBio HiFi, phased with Hi-C	copy number per parental haplotype, with loss-of-heterozygosity (LOH) intervals in a second file
NYGC somatic pipeline, BIC-seq2	Illumina WGS	log2 tumor-versus-normal copy ratio, and the genes the segment covers
DRAGEN	Illumina WGS	integer copy number, minor-haplotype copy number and minor allele frequency

Read the other callsets against the benchmark CNV BED that part 1 adds, whose copy numbers are absolute, so CN 2 marks a diploid region.

Loading DRAGEN copy-number segments

DRAGEN's CNV calls load as an indexed VCF, one record per segment. Record IDs read DRAGEN:CNLOH:chr9:22631070-22939213 (copy-neutral loss of heterozygosity), so the label takes the class from the second field:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "VariantTrack",
  "trackId": "hg008t_dragen_cnv",
  "name": "HG008-T DRAGEN somatic CNV (Illumina)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/dragen_4.2.4_HG008-mosaic_tumor.cnv.vcf.gz"
  },
  "displayDefaults": {
    "labels": { "name": "jexl:split(feature.name,':')[1]" }
  }
}

CLI (add-track)

jbrowse add-track https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/dragen_4.2.4_HG008-mosaic_tumor.cnv.vcf.gz \
  --trackId hg008t_dragen_cnv \
  --name "HG008-T DRAGEN somatic CNV (Illumina)" \
  --assemblyNames GRCh38_GIABv3 \
  --displayDefaults "{\"labels\":{\"name\":\"jexl:split(feature.name,':')[1]\"}}"

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "VariantTrack",
  "trackId": "hg008t_dragen_cnv",
  "name": "HG008-T DRAGEN somatic CNV (Illumina)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "VcfTabixAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/DRAGEN-v4.2.4_ILMN-WGS_20240312/standard/dragen_4.2.4_HG008-mosaic_tumor.cnv.vcf.gz"
  },
  "displayDefaults": {
    "labels": { "name": "jexl:split(feature.name,':')[1]" }
  }
}

NYGC copy-number segments and log2 copy ratio

C-GIAB publishes the NYGC CNV output in two forms. HG008-T--HG008-N.cnv.annotated.v7.final.bed loads as is, because the adapter reads column names from its # header line.

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "FeatureTrack",
  "trackId": "hg008t_nygc_cnv",
  "name": "HG008-T NYGC CNV calls, annotated (BIC-seq2)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/HG008-T--HG008-N.cnv.annotated.v7.final.bed"
  },
  "displayDefaults": {
    "displayMode": "compact",
    "color": {
      "field": "type",
      "domain": ["DEL", "DUP"],
      "range": ["#2166ac", "#b2182b"],
      "labels": ["Loss (DEL)", "Gain (DUP)"],
      "title": "Call"
    },
    "labels": { "name": "jexl:feature.type+' '+feature.cytoband" }
  }
}

CLI (add-track)

jbrowse add-track https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/HG008-T--HG008-N.cnv.annotated.v7.final.bed \
  --trackId hg008t_nygc_cnv \
  --name "HG008-T NYGC CNV calls, annotated (BIC-seq2)" \
  --assemblyNames GRCh38_GIABv3 \
  --displayDefaults "{\"displayMode\":\"compact\",\"color\":{\"field\":\"type\",\"domain\":[\"DEL\",\"DUP\"],\"range\":[\"#2166ac\",\"#b2182b\"],\"labels\":[\"Loss (DEL)\",\"Gain (DUP)\"],\"title\":\"Call\"},\"labels\":{\"name\":\"jexl:feature.type+' '+feature.cytoband\"}}"

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "FeatureTrack",
  "trackId": "hg008t_nygc_cnv",
  "name": "HG008-T NYGC CNV calls, annotated (BIC-seq2)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NYGC-somatic-pipeline_20240412/GRCh38-GIABv3/HG008-T--HG008-N.cnv.annotated.v7.final.bed"
  },
  "displayDefaults": {
    "displayMode": "compact",
    "color": {
      "field": "type",
      "domain": ["DEL", "DUP"],
      "range": ["#2166ac", "#b2182b"],
      "labels": ["Loss (DEL)", "Gain (DUP)"],
      "title": "Call"
    },
    "labels": { "name": "jexl:feature.type+' '+feature.cytoband" }
  }
}

HG008-T--HG008-N.bicseq2.txt is the same segmentation with one log2 ratio per segment, which one awk command converts to a bedGraph:

# column 9 is log2.copyRatio; $2-1 converts the 1-based start to 0-based
awk 'NR>1 {printf "%s\t%d\t%d\t%.4f\n", $1, $2-1, $3, $9}' \
  HG008-T--HG008-N.bicseq2.txt > HG008-T_bicseq2_log2ratio.bedgraph

We'll plot it as bars from zero on a fixed axis, so a step means the same thing from one window to the next. A homozygous deletion has no reads and so no finite ratio, and a balanced region sits above zero because BIC-seq2 normalizes on total read counts and HG008-T is hypodiploid.

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "QuantitativeTrack",
  "trackId": "hg008t_bicseq2",
  "name": "HG008-T copy ratio, segmented (NYGC BIC-seq2, log2 T/N)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedGraphAdapter",
    "uri": "HG008-T_bicseq2_log2ratio.bedgraph"
  },
  "displayDefaults": {
    "mark": "bar",
    "scales": {
      "y": {
        "domainMin": -2,
        "domainMax": 2,
        "grid": true,
        "title": "log2 tumor/normal"
      }
    }
  }
}

CLI (add-track)

jbrowse add-track HG008-T_bicseq2_log2ratio.bedgraph \
  --trackId hg008t_bicseq2 \
  --name "HG008-T copy ratio, segmented (NYGC BIC-seq2, log2 T/N)" \
  --assemblyNames GRCh38_GIABv3 \
  --displayDefaults '{"mark":"bar","scales":{"y":{"domainMin":-2,"domainMax":2,"grid":true,"title":"log2 tumor/normal"}}}' \
  --load copy

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "QuantitativeTrack",
  "trackId": "hg008t_bicseq2",
  "name": "HG008-T copy ratio, segmented (NYGC BIC-seq2, log2 T/N)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedGraphAdapter",
    "uri": "HG008-T_bicseq2_log2ratio.bedgraph"
  },
  "displayDefaults": {
    "mark": "bar",
    "scales": {
      "y": {
        "domainMin": -2,
        "domainMax": 2,
        "grid": true,
        "title": "log2 tumor/normal"
      }
    }
  }
}

HG008-T_bicseq2_log2ratio.bedgraph is relative to a config.json. Replace it with its URL or its path on this computer.

Loading Wakhan copy number per haplotype

Wakhan's HG008_HiFi_HiC_copynumbers_segments.bed is long format, one row per haplotype, with no # on its column-name line:

chr	start	end	copynumber_state	coverage	haplotype
chr1	0	23750000	2	106.025	1
chr1	23750001	119650000	0.72	58.025	1

The haplotype column assigns each segment to a row, so we use LinearMultiRowFeatureDisplay and set rows to haplotype. The adapter names its columns with columnNames:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "FeatureTrack",
  "trackId": "hg008t_wakhan_hifi_hic",
  "name": "HG008-T Wakhan copy number per haplotype (HiFi + Hi-C)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi-HiC_Wakhan-CNA_20240424/bed_output/HG008_HiFi_HiC_copynumbers_segments.bed",
    "columnNames": [
      "chrom",
      "start",
      "end",
      "copynumber_state",
      "coverage",
      "haplotype"
    ]
  },
  "displays": [
    {
      "type": "LinearMultiRowFeatureDisplay",
      "rows": "haplotype",
      "color": {
        "field": "copynumber_state",
        "scale": "threshold",
        "domain": [0.5, 1.5],
        "range": ["#2166ac", "#bdbdbd", "#f4a582"],
        "labels": ["Haplotype lost (0)", "One copy", "Two or more copies"],
        "title": "Copy number per haplotype"
      }
    }
  ]
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "FeatureTrack",
  "trackId": "hg008t_wakhan_hifi_hic",
  "name": "HG008-T Wakhan copy number per haplotype (HiFi + Hi-C)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi-HiC_Wakhan-CNA_20240424/bed_output/HG008_HiFi_HiC_copynumbers_segments.bed",
    "columnNames": [
      "chrom",
      "start",
      "end",
      "copynumber_state",
      "coverage",
      "haplotype"
    ]
  },
  "displays": [
    {
      "type": "LinearMultiRowFeatureDisplay",
      "rows": "haplotype",
      "color": {
        "field": "copynumber_state",
        "scale": "threshold",
        "domain": [0.5, 1.5],
        "range": ["#2166ac", "#bdbdbd", "#f4a582"],
        "labels": ["Haplotype lost (0)", "One copy", "Two or more copies"],
        "title": "Copy number per haplotype"
      }
    }
  ]
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "FeatureTrack",
  "trackId": "hg008t_wakhan_hifi_hic",
  "name": "HG008-T Wakhan copy number per haplotype (HiFi + Hi-C)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BedAdapter",
    "uri": "https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/data_somatic/HG008/Liss_lab/analysis/NIH_HiFi-HiC_Wakhan-CNA_20240424/bed_output/HG008_HiFi_HiC_copynumbers_segments.bed",
    "columnNames": [
      "chrom",
      "start",
      "end",
      "copynumber_state",
      "coverage",
      "haplotype"
    ]
  },
  "displays": [
    {
      "type": "LinearMultiRowFeatureDisplay",
      "rows": "haplotype",
      "color": {
        "field": "copynumber_state",
        "scale": "threshold",
        "domain": [0.5, 1.5],
        "range": ["#2166ac", "#bdbdbd", "#f4a582"],
        "labels": ["Haplotype lost (0)", "One copy", "Two or more copies"],
        "title": "Copy number per haplotype"
      }
    }
  ]
}

A copynumber_state of 0 marks a haplotype lost across an arm (LOH), and 1 is the normal single copy. Advanced → Edit plot... in the track menu shows rows and color as text and applies edits to the open track.

Building depth-per-bin and B-allele frequency tracks

HiFiCNV writes a binned depth track from the tumor reads:

# the depth output is <prefix>.<sample>.depth.bw, named for the --bam sample,
#   so this run writes hificnv.<sample>.depth.bw
# the hosted demo renames it HG008-T.hificnv.depth.bw, the uri below
# --maf: the Clair3 tumor small-variant VCF from the C-GIAB Wakhan run;
#   HiFiCNV reads AD from it for the allele-frequency output
# --bam: the reads, for depth
hificnv --bam HG008-T.cram --ref GRCh38.fa --maf tumor_smallvariants.vcf.gz \
  --output-prefix hificnv

We'll load the depth as points, the Scatter plot type:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "QuantitativeTrack",
  "trackId": "hg008_depth",
  "name": "HG008-T HiFiCNV depth",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T.hificnv.depth.bw"
  },
  "displayDefaults": { "mark": "point", "size": 1 }
}

CLI (add-track)

jbrowse add-track HG008-T.hificnv.depth.bw \
  --trackId hg008_depth \
  --name "HG008-T HiFiCNV depth" \
  --assemblyNames GRCh38_GIABv3 \
  --displayDefaults '{"mark":"point","size":1}' \
  --load copy

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "QuantitativeTrack",
  "trackId": "hg008_depth",
  "name": "HG008-T HiFiCNV depth",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T.hificnv.depth.bw"
  },
  "displayDefaults": { "mark": "point", "size": 1 }
}

HG008-T.hificnv.depth.bw is relative to a config.json. Replace it with its URL or its path on this computer.

To compare the depth with the callsets, draw it with Plot type → XY plot and a fixed axis from Y axis... → Range, so a halving reads as a level. Open chr9:21,850,000-23,050,000, around CDKN2A, with the depth above the four CNV callsets:

Four published CNV callsets over chr9p21.3, under the HiFiCNV depth.

B-allele frequency (BAF) is the fraction of tumor reads with the alternate allele, drawn unfolded. A balanced region is one band at 0.5, and a region with LOH (one parental copy gone) splits into two bands at 0 and 1. Build it by piling up the tumor reads at the sites the normal calls heterozygous and taking the alt fraction:

# het sites come from the normal, because LOH sites are homozygous in the tumor
bcftools view -g het -Oz -o hets.vcf.gz normal.deepvariant.vcf.gz
tabix -p vcf hets.vcf.gz
cut -f1,2 GRCh38.fa.fai > GRCh38.chrom.sizes

# -q 1 drops multi-mapped reads, -Q 0 leaves HiFi base qualities alone
bcftools mpileup -f GRCh38.fa -T hets.vcf.gz -a AD -q 1 -Q 0 tumor.bam |
  bcftools query -f '%CHROM\t%POS\t[%AD]\n' |
  # unfolded alt fraction at sites with depth 10 or more
  awk -F'[\t,]' '{d=$3+$4; if (d>=10) printf "%s\t%d\t%d\t%.4f\n",$1,$2-1,$2,$4/d}' |
  LC_COLLATE=C sort -k1,1 -k2,2n > baf.bedgraph
bedGraphToBigWig baf.bedgraph GRCh38.chrom.sizes HG008-T_baf.bcftools.bw

Plot it with Scatter over a fixed 0 to 1 range.

Chromosome 3: the segmented copy ratio, the HiFiCNV depth and B-allele frequency over the benchmark CNV calls.

Drawing individual BAF points when zoomed out

Zoomed out, the default bigWig summary paints an LOH arm as a solid block of full height. A small resolutionMultiplier makes the adapter fetch raw per-site values at the zoom levels of these figures:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "QuantitativeTrack",
  "trackId": "HG008-T_baf",
  "name": "HG008-T B-allele frequency (BAF)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T_baf.bcftools.bw",
    "resolutionMultiplier": 0.001
  },
  "displayDefaults": {
    "mark": "point",
    "size": 1,
    "scales": { "y": { "domainMin": 0, "domainMax": 1 } }
  }
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "QuantitativeTrack",
  "trackId": "HG008-T_baf",
  "name": "HG008-T B-allele frequency (BAF)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T_baf.bcftools.bw",
    "resolutionMultiplier": 0.001
  },
  "displayDefaults": {
    "mark": "point",
    "size": 1,
    "scales": { "y": { "domainMin": 0, "domainMax": 1 } }
  }
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "QuantitativeTrack",
  "trackId": "HG008-T_baf",
  "name": "HG008-T B-allele frequency (BAF)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "BigWigAdapter",
    "uri": "HG008-T_baf.bcftools.bw",
    "resolutionMultiplier": 0.001
  },
  "displayDefaults": {
    "mark": "point",
    "size": 1,
    "scales": { "y": { "domainMin": 0, "domainMax": 1 } }
  }
}

HG008-T_baf.bcftools.bw is relative to a config.json. Replace it with its URL or its path on this computer.

Checking copy number at four pancreatic cancer driver genes

In pancreatic ductal adenocarcinoma the recurrently altered genes are KRAS, CDKN2A, TP53 and SMAD4 (Waddell et al. 2015, Bailey et al. 2016). Each copy-number figure below draws the gene's MANE Select (standard reference) transcript under the tracks.

For a first check, load the tumor and normal coverage from goleft indexcov as one multi-wiggle track, one bigWig per sample. indexcov scales each sample by its median depth, so the two compare directly. It writes a per-sample table, so the track below reads the demo's bigWig copies; swap each uri for your sample's bigWig:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_cnv_indexcov",
  "name": "HG008 normal vs tumor coverage (indexcov)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw"
        }
      },
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw"
        }
      }
    ]
  }
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_cnv_indexcov",
  "name": "HG008 normal vs tumor coverage (indexcov)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw"
        }
      },
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw"
        }
      }
    ]
  }
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_cnv_indexcov",
  "name": "HG008 normal vs tumor coverage (indexcov)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw"
        }
      },
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw"
        }
      }
    ]
  }
}

Plot type → Overlapping → Scatter in its track menu draws the two samples as points in one band, with a key naming each sample's color. Y axis... → Range with 0 and 3 stops indexcov's centromere spikes from flattening every plateau.

Zoom to a region and open the benchmark CNV BED. Coverage shows where the copy number steps and BAF the allelic balance across each step.

Plot type → Overlapping → Scatter on the coverage track, drawing the two rows as one band of points.

Video

Open the session the video starts in ↗, then take the steps it shows:

Tumor and normal on stacked rows, each autoscaled on its own
Overlay the two rows as points on one axis
The tumor sits above its normal on 5p, below it on 5q

Steps

Open this view in JBrowse Web ↗ ·

Open in JBrowse Desktop ↗

Needs JBrowse Desktop 5.0 or newer. If nothing opens, copy the link and paste it into Desktop's Open JBrowse Web link..., on the start screen or under File → Session.

https://jbrowse.org/code/jb2/main/?config=https%3A%2F%2Fjbrowse.org%2Fdemos%2Fcgiab%2Fconfig.json&session=spec-%7B%22sessionTracks%22%3A%5B%7B%22type%22%3A%22MultiQuantitativeTrack%22%2C%22trackId%22%3A%22hg008_cnv_indexcov%22%2C%22name%22%3A%22HG008+normal+vs+tumor+coverage+%28indexcov%29%22%2C%22assemblyNames%22%3A%5B%22GRCh38_GIABv3%22%5D%2C%22adapter%22%3A%7B%22type%22%3A%22MultiWiggleAdapter%22%2C%22subadapters%22%3A%5B%7B%22name%22%3A%22HG008-N+%28normal%29%22%2C%22type%22%3A%22BigWigAdapter%22%2C%22bigWigLocation%22%3A%7B%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fcgiab%2FHG008-N_indexcov.bw%22%2C%22locationType%22%3A%22UriLocation%22%7D%7D%2C%7B%22name%22%3A%22HG008-T+%28tumor%29%22%2C%22type%22%3A%22BigWigAdapter%22%2C%22bigWigLocation%22%3A%7B%22uri%22%3A%22https%3A%2F%2Fjbrowse.org%2Fdemos%2Fcgiab%2FHG008-T_indexcov.bw%22%2C%22locationType%22%3A%22UriLocation%22%7D%7D%5D%7D%7D%5D%2C%22views%22%3A%5B%7B%22type%22%3A%22LinearGenomeView%22%2C%22assembly%22%3A%22GRCh38_GIABv3%22%2C%22loc%22%3A%22chr5%22%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22hg008_cnv_indexcov%22%2C%22type%22%3A%22LinearWiggleDisplay%22%2C%22height%22%3A200%7D%5D%7D%5D%7D&sessionName=JBrowse+docs%3A+sv_cgiab%2Fcopy_number_layout

The short route: open the view in JBrowse Web, where File → Open track... adds your own files beside its hosted genome and tracks.

From scratch with your own data, the steps behind the figure:

Open your genome: on the JBrowse Desktop start screen click Open new genome (or Show all available genomes to pick a hosted one). For JBrowse Web, jbrowse add-assembly puts it in your config.json.This figure uses GRCh38_GIABv3, loaded from a bgzip-compressed FASTA (.fa.gz + .fai + .gzi).
Add a track: check one your config has in the track selector, or File → Open track... to paste a URL or choose a local file.This figure uses “HG008 normal vs tumor coverage (indexcov)”.
Type your region of interest into the location box and press Enter.This figure is at chr5.

CLI

A figure adds its tracks to one session. The jbrowse CLI writes the same tracks into a config.json instead, where every session that opens it has them: add-track where flags cover the whole track, add-track-json where they do not.

jbrowse add-track-json '{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_cnv_indexcov",
  "name": "HG008 normal vs tumor coverage (indexcov)",
  "assemblyNames": [
    "GRCh38_GIABv3"
  ],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
          "locationType": "UriLocation"
        }
      },
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "bigWigLocation": {
          "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
          "locationType": "UriLocation"
        }
      }
    ]
  }
}'

Run these where the config.json is, or add --out <dir>, and point each uri at your own file. The config needs GRCh38_GIABv3 already — jbrowse add-assembly adds yours. The location and the settings the steps carry are session state rather than track config — that half is the Spec tab, or jbrowse set-default-session.

Spec

This session spec draws the figure. It goes after &session=spec- on a JBrowse Web link that loads https://jbrowse.org/demos/cgiab/config.json, which is what the Web button above opens.

{
  "sessionTracks": [
    {
      "type": "MultiQuantitativeTrack",
      "trackId": "hg008_cnv_indexcov",
      "name": "HG008 normal vs tumor coverage (indexcov)",
      "assemblyNames": [
        "GRCh38_GIABv3"
      ],
      "adapter": {
        "type": "MultiWiggleAdapter",
        "subadapters": [
          {
            "name": "HG008-N (normal)",
            "type": "BigWigAdapter",
            "bigWigLocation": {
              "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
              "locationType": "UriLocation"
            }
          },
          {
            "name": "HG008-T (tumor)",
            "type": "BigWigAdapter",
            "bigWigLocation": {
              "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
              "locationType": "UriLocation"
            }
          }
        ]
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "GRCh38_GIABv3",
      "loc": "chr5",
      "tracks": [
        {
          "trackId": "hg008_cnv_indexcov",
          "type": "LinearWiggleDisplay",
          "height": 200
        }
      ]
    }
  ]
}

Notebook

The same view with jbrowse-anywidget, from the config the figure loads. Swap a track's uri for your own file.

from jbrowse_anywidget import JBrowseApp, fetch_hub

config = fetch_hub("https://jbrowse.org/demos/cgiab/config.json")
app = JBrowseApp(
    assemblies=config["assemblies"],
    tracks=config.get("tracks", []) + [
        {
            "type": "MultiQuantitativeTrack",
            "trackId": "hg008_cnv_indexcov",
            "name": "HG008 normal vs tumor coverage (indexcov)",
            "assemblyNames": [
                "GRCh38_GIABv3"
            ],
            "adapter": {
                "type": "MultiWiggleAdapter",
                "subadapters": [
                    {
                        "name": "HG008-N (normal)",
                        "type": "BigWigAdapter",
                        "bigWigLocation": {
                            "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
                            "locationType": "UriLocation"
                        }
                    },
                    {
                        "name": "HG008-T (tumor)",
                        "type": "BigWigAdapter",
                        "bigWigLocation": {
                            "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
                            "locationType": "UriLocation"
                        }
                    }
                ]
            }
        }
    ],
    views=[
        {
            "type": "LinearGenomeView",
            "assembly": "GRCh38_GIABv3",
            "loc": "chr5",
            "tracks": [
                {
                    "trackId": "hg008_cnv_indexcov",
                    "type": "LinearWiggleDisplay",
                    "height": 200
                }
            ]
        }
    ],
)
app  # display the widget

Image

jbrowse-img draws the same view as an SVG, from the command line and without a browser. Point --config at your own config, or swap a track for your own file with --bam, --vcfgz and the other file flags.

cat > tracks.json <<'JSON'
[
  {
    "type": "MultiQuantitativeTrack",
    "trackId": "hg008_cnv_indexcov",
    "name": "HG008 normal vs tumor coverage (indexcov)",
    "assemblyNames": [
      "GRCh38_GIABv3"
    ],
    "adapter": {
      "type": "MultiWiggleAdapter",
      "subadapters": [
        {
          "name": "HG008-N (normal)",
          "type": "BigWigAdapter",
          "bigWigLocation": {
            "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
            "locationType": "UriLocation"
          }
        },
        {
          "name": "HG008-T (tumor)",
          "type": "BigWigAdapter",
          "bigWigLocation": {
            "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
            "locationType": "UriLocation"
          }
        }
      ]
    }
  }
]
JSON

npx @jbrowse/img --config https://jbrowse.org/demos/cgiab/config.json \
  --tracks tracks.json \
  --assembly GRCh38_GIABv3 --loc chr5 \
  --track hg008_cnv_indexcov display:LinearWiggleDisplay '{"height":200}' \
  --width 1920 --out figure.svg

--out figure.png writes a PNG instead, through rsvg-convert (apt install librsvg2-bin, brew install librsvg).

Agent

Hand this to a coding agent. It rebuilds the figure above headlessly, and the session file is then the thing to edit: change the location or a track's settings, or add your own track under sessionTracks, and rerun.

cat > session.json <<'JSON'
{
  "sessionTracks": [
    {
      "type": "MultiQuantitativeTrack",
      "trackId": "hg008_cnv_indexcov",
      "name": "HG008 normal vs tumor coverage (indexcov)",
      "assemblyNames": [
        "GRCh38_GIABv3"
      ],
      "adapter": {
        "type": "MultiWiggleAdapter",
        "subadapters": [
          {
            "name": "HG008-N (normal)",
            "type": "BigWigAdapter",
            "bigWigLocation": {
              "uri": "https://jbrowse.org/demos/cgiab/HG008-N_indexcov.bw",
              "locationType": "UriLocation"
            }
          },
          {
            "name": "HG008-T (tumor)",
            "type": "BigWigAdapter",
            "bigWigLocation": {
              "uri": "https://jbrowse.org/demos/cgiab/HG008-T_indexcov.bw",
              "locationType": "UriLocation"
            }
          }
        ]
      }
    }
  ],
  "views": [
    {
      "type": "LinearGenomeView",
      "assembly": "GRCh38_GIABv3",
      "loc": "chr5",
      "tracks": [
        {
          "trackId": "hg008_cnv_indexcov",
          "type": "LinearWiggleDisplay",
          "height": 200
        }
      ]
    }
  ]
}
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/demos/cgiab/config.json \
  --width 1920 --height 520 \
  --spec session.json -o figure.png

Using JBrowse with AI agents covers the rest: hosted genomes to point it at, and why waiting for the render is the part that goes wrong.

Chromosome 5: the segmented copy ratio, tumor and normal coverage as overlapping scatter, the BAF and the benchmark CNV calls.

CDKN2A: homozygous deletion

Navigate to CDKN2A on chr9. The benchmark calls a focal ~20 kb homozygous deletion over the gene (SV_75, CN 0, no copies left), inside a larger single-copy-loss arm (CNA_14, 0+1 copies on the two haplotypes) where depth is already halved (Wagner et al. 2026).

Load the tumor and matched normal per-base coverage as one multi-quantitative track, one row per sample, with an explicit score range. The two bigWigs are the megadepth outputs for each sample's CRAM; swap in yours:

Config file

Goes in the tracks array of config.json. See Tracks.

{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_tn_perbase",
  "name": "HG008 tumor vs matched normal coverage (per-base)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "color": "#e41a1c",
        "bigWigLocation": { "uri": "HG008-T.cram.all.bw" }
      },
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "color": "#377eb8",
        "bigWigLocation": { "uri": "HG008-N.cram.all.bw" }
      }
    ]
  },
  "displayDefaults": {
    "mark": "bar",
    "extent": "none",
    "scales": { "y": { "domainMin": 0, "domainMax": 80, "grid": false } },
    "height": 280
  }
}

CLI (add-track-json)

jbrowse add-track-json '{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_tn_perbase",
  "name": "HG008 tumor vs matched normal coverage (per-base)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "color": "#e41a1c",
        "bigWigLocation": { "uri": "HG008-T.cram.all.bw" }
      },
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "color": "#377eb8",
        "bigWigLocation": { "uri": "HG008-N.cram.all.bw" }
      }
    ]
  },
  "displayDefaults": {
    "mark": "bar",
    "extent": "none",
    "scales": { "y": { "domainMin": 0, "domainMax": 80, "grid": false } },
    "height": 280
  }
}'

In the app

In JBrowse Desktop, or in any running JBrowse Web session, open a view on this track’s assembly, then File → Open track..., choose Add track from pasted JSON, and paste:

{
  "type": "MultiQuantitativeTrack",
  "trackId": "hg008_tn_perbase",
  "name": "HG008 tumor vs matched normal coverage (per-base)",
  "assemblyNames": ["GRCh38_GIABv3"],
  "adapter": {
    "type": "MultiWiggleAdapter",
    "subadapters": [
      {
        "name": "HG008-T (tumor)",
        "type": "BigWigAdapter",
        "color": "#e41a1c",
        "bigWigLocation": { "uri": "HG008-T.cram.all.bw" }
      },
      {
        "name": "HG008-N (normal)",
        "type": "BigWigAdapter",
        "color": "#377eb8",
        "bigWigLocation": { "uri": "HG008-N.cram.all.bw" }
      }
    ]
  },
  "displayDefaults": {
    "mark": "bar",
    "extent": "none",
    "scales": { "y": { "domainMin": 0, "domainMax": 80, "grid": false } },
    "height": 280
  }
}

HG008-T.cram.all.bw, HG008-N.cram.all.bw are relative to a config.json. Replace each with its URL or its path on this computer.

Thin lines across the gap in the read pileup are reads with the deletion.

The benchmark's total_copy_number is absolute, so CN 2 is diploid; 9p has already lost a copy, so CN 1 is the local background here. Widen the view several hundred kilobases right to read CN 2 against it.

Tumor and normal coverage, the pileup and the CNV calls over CDKN2A.

Chromosome 17: two kinds of loss of heterozygosity

Chromosome 17 has two LOH states, split partway along the q-arm. Open it whole with the depth track above the BAF:

The p-arm (covering TP53) and the start of the q-arm are a single-copy loss with LOH (CNA_20, CN 1, 1+0).
The rest of the q-arm is copy-neutral LOH (CNA_21, CN 2, 2+0): one haplotype lost, the other duplicated.

Chromosome 17: the segmented copy ratio, the HiFiCNV depth, the BAF and the benchmark CNV calls.

Together, depth and BAF separate these states:

depth	BAF	Interpretation
flat (CN 2)	one band at 0.5	balanced diploid
flat (CN 2)	split to 0, 1	copy-neutral LOH
halved	split to 0, 1	single-copy loss with LOH
raised	1/3 and 2/3	allelic gain

The benchmark BED's hap1_copy_number and hap2_copy_number columns give the 1+0 and 2+0 splits. Click a CNV feature to see both.

KRAS gain and SMAD4 loss

Navigate to KRAS on chr12. It sits in a gain (SV_101, CN 3, 2+1): a 2 Mb tandem duplication that includes the G12V-mutated copy (Wagner et al. 2026).

KRAS's MANE Select transcript over the copy ratio, depth and BAF, above the CNV calls.

SMAD4 on 18q is a single-copy loss with LOH (CNA_48, CN 1, 0+1), like TP53. The balanced p-arm and the matched normal are the two controls. Leave the copy-ratio track's color unset (one color above the origin of 0, another below) with a symmetric axis, so a step down and a step up fill equally.

SMAD4's MANE Select transcript over the copy ratio, tumor and normal coverage and the BAF, above the CNV calls.

Reproduce it end to end

build_sv_visualization_cgiab.sh writes the coverage, depth and B-allele frequency files above as part of the run that part 1 describes.

Citations

Bailey et al. (2016). Genomic analyses identify molecular subtypes of pancreatic cancer
Diesh et al. (2023). JBrowse 2: A Modular Genome Browser with Views of Synteny and Structural Variation
McDaniel et al. (2025). Development and Extensive Sequencing of a Broadly-Consented Genome in a Bottle Matched Tumor-Normal Pair
Waddell et al. (2015). Whole genomes redefine the mutational landscape of pancreatic cancer
Wagner et al. (2026). A complete human pancreatic cancer genome

Feedback on this tutorial is welcome: contact us.

Structural variants (Cancer GIAB) part 2: copy number

Prerequisites#

The data#

Installing megadepth and HiFiCNV#

Coverage bigWigs from the CRAMs#

Copy number from the published callsets#

Loading DRAGEN copy-number segments#

NYGC copy-number segments and log2 copy ratio#

Loading Wakhan copy number per haplotype#

Building depth-per-bin and B-allele frequency tracks#

Drawing individual BAF points when zoomed out#

Checking copy number at four pancreatic cancer driver genes#

CDKN2A: homozygous deletion#

Chromosome 17: two kinds of loss of heterozygosity#

KRAS gain and SMAD4 loss#

Reproduce it end to end#

See also#

Citations#

Prerequisites

The data

Installing megadepth and HiFiCNV

Coverage bigWigs from the CRAMs

Copy number from the published callsets

Loading DRAGEN copy-number segments

NYGC copy-number segments and log2 copy ratio

Loading Wakhan copy number per haplotype

Building depth-per-bin and B-allele frequency tracks

Drawing individual BAF points when zoomed out

Checking copy number at four pancreatic cancer driver genes

CDKN2A: homozygous deletion

Chromosome 17: two kinds of loss of heterozygosity

KRAS gain and SMAD4 loss

Reproduce it end to end

See also

Citations